Annexure 1: Kriel Atmopsheric Impact Report (December 2013)
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Transcript of Annexure 1: Kriel Atmopsheric Impact Report (December 2013)
i
ANNEXURE C
Report issued by
Report issued to uMoya-NILU Consulting (Pty) Ltd
P O Box 20622
Durban North, 4016
South Africa
Eskom
P O Box 1091
Johannesburg, 2001
South Africa
M Zunckel
A Raghunandan
December 2013
ATMOSPHERIC IMPACT REPORT
In support of
Eskom’s application for postponement of the Minimum
Emission Standards compliance timeframes for the Kriel Power
Station
ii
This report has been produced for Eskom by uMoya-NILU Consulting (Pty) Ltd. The intellectual property
contained in this report remains vested in uMoya-NILU Consulting (Pty) Ltd. No part of the report may be
reproduced in any manner without written permission from uMoya-NILU Consulting (Pty) Ltd and Eskom.
When used in a reference this document should be cited as follows:
uMoya-NILU (2013): Atmospheric Impact Report in support of Eskom’s application for postponement of the
Minimum Emission Standards compliance timeframes for the Kriel Power Station, Report No. uMN0046-
2013, December 2013.
i
EXECUTIVE SUMMARY
Eskom’s coal-fired Kriel Power Station in Mpumalanga Province has a base generation capacity of 3000
MW. Power generation is a Listed Activity in terms of Section 21 of the NEMAQA and Kriel should
comply with the prescribed Minimum Emission Standards (MES) for existing plants by 2015 and for new
plants by 2020. Eskom contends that full compliance with the MES is not in the national interest, given
the unintended negative consequences of full compliance. Kriel already achieves the Sulphur dioxide
(SO2) limit (MES for ‘existing plant’). However, Kriel Power Station will not be able to comply with the
‘new plant’ MES for SO2, or with the ‘existing plant’ or ‘new plant’ NOx MES.. Plans are underway to
reduce Particulate Matter (PM) emissions from Kriel so that Kriel will comply with the existing and new
plant limits. However, the emission reductions will only be fully realised by April 2025. The purpose of
this AIR is to present an assessment of the ambient air quality implications of the postponement
application and the requested emissions limits for human health and the environment.
An analysis of ambient SO2 concentrations measured at the Kriel Village (situated 7km east of Kriel
Power Station), Elandsfontein, and Komati monitoring stations, indicates compliance with the hourly,
daily and annual average NAAQS for SO2. Full compliance with the 10-minute NAAQS for SO2 was
recorded at Kriel Village Monitoring Station (10-minute data is not recorded yet at the other monitoring
stations). Ambient PM measured at Kriel, Komati and Elandsfontein monitoring stations indicates non-
compliance with both the daily and annual NAAQS However, modelling shows that Kriel Power Station
is seen to contribute only marginally to the measured concentrations at all three monitoring sites,
bearing in mind that the bulk of the contribution to PM10 concentrations arises from low level sources,
especially domestic fuel use. Ambient NOx measured at Kriel Village, Elandsfontein, and Komati
monitoring stations indicates full compliance with the hourly and annual NO2 NAAQS.
Dispersion modelling shows that current emissions from Kriel Power Station do not result in non-
compliance with SO2, NOx or PM ambient air quality standards. Similarly, the requested emission limits
for NOx, PM and SO2 will not result in non-compliance with ambient air quality standards
Cumulatively, the modelled actual current emissions for Eskom’s Power Stations on the Northern
Highveld combined comply with the NAAQS for SO2, NOx and PM10 and in all cases ambient
concentrations are significantly lower than the NAAQS. If all the power stations in the Northern Highveld
emit continuously at the requested emission limits (a theoretical scenario), predictions show that there
will still be compliance with the PM and NOx NAAQS, and with the annual average SO2 NAAQS.
However, if power stations continuously emit at the requested SO2 emission limits, there will be non-
compliance with the 24-hour and 1-hour SO2 concentrations over fairly large regions in the Northern
Highveld. The number of exceedences per annum is also significantly higher than that permissible in
terms of the NAAQS.
Modelling results confirm that Eskom’s requested PM emission limits cumulatively will not result in
additional health risk in the areas potentially impacted upon by the emissions, as both the annual
average and 99th percentile 24-hour concentrations fall well below the NAAQS limit values. A similar
picture is presented for the cumulative NO2 emissions which also comply with the NAAQS limit values
and maximum permissible exceedences per annum, thus augmenting the statement that Eskom’s
requested NOx emission limits will not result in deterioration in the health risk that currently prevails.
While cumulatively the annual average ambient SO2 concentration falls within the NAAQS limit value
considering Eskom’s requested SO2 emission limits, the 99th percentile 24-hour and 1-hour
concentrations do not, and significantly exceed the permissible number of exceedences per annum.
Thus, the risk exists of unacceptable potential health risk. This finding, however, must be seen in the
ii
light that the predicted concentrations are probably an exaggeration of what actually happens in practice
because when the SO2 emission sources are combined, the model error brought about by modelling
the maximum emissions rates at the power stations individually, is exaggerated further still because the
chances of all the sources operating at the requested emissions limits for an entire year is highly
improbable if not impossible.
iii
LIST OF ACRONYMS
µm 1 µm = 10-6 m
AEL Atmospheric Emission License
AIR Atmospheric Impact Report
APPA Atmospheric Pollution Prevention Act, 1965 (Act No. 45 of 1965)
AQMP Air Quality Management Plan
BID Background Information Document
DEA Department of Environmental Affairs
DoE Department of Energy
ESP Electrostatic precipitator
FFP Fabric Filter Plant
FGD Flue gas desulphurisation
IRP Integrated Resource Plan
LNB Low NOx Burner
LPG Liquid Petroleum Gas
NAAQS National Ambient Air Quality Standards
NEMAQA National Environment Management: Air Quality Act, 2004 (Act No. 39 of 2004)
NEMA National Environmental Management Act, 1998 (Act No. 107 of 1998)
NO Nitrogen oxide
NO2 Nitrogen dioxide
NOX Oxides of nitrogen (NOX = NO + NO2)
OFA Overfire Air
PM Particulate Matter
PM10 Particulate Matter with a diameter of less than 10 µm
PM2.5 Particulate Matter with a diameter of less than 2.5 µm
SO2 Sulphur Dioxide
TSP Total Suspended Particulates
WHO World Health Organisation
iv
TABLE OF CONTENTS
EXECUTIVE SUMMARY ......................................................................................................................... i
LIST OF ACRONYMS ........................................................................................................................... iii
TABLE OF CONTENTS ........................................................................................................................ iv
TABLES ................................................................................................................................................. vi
FIGURES ............................................................................................................................................... vi
1. Enterprise Details .......................................................................................................................... 9
1.1 Enterprise Details .................................................................................................................... 9
1.2 Location and extent of the Plant............................................................................................ 10
1.3 Atmospheric Emission License and Other Authorisations .................................................... 11
1.3.1 Minimum Emission Standards ....................................................................................... 12
1.3.2 National Ambient Air Quality Standards (NAAQS) ........................................................ 12
2. Nature of the Process ................................................................................................................. 14
2.1 Listed Activity or Activities ..................................................................................................... 14
2.2 Process Description .............................................................................................................. 14
2.2.1 Atmospheric emissions resulting from power generation ............................................. 15
2.3 Unit Processes ...................................................................................................................... 16
3. Technical Information ................................................................................................................. 17
3.1 Raw Materials Used .............................................................................................................. 17
3.2 Appliances and Abatement Equipment Control Technology ................................................ 17
4. Atmospheric emissions .............................................................................................................. 18
4.1 Point source parameters ....................................................................................................... 18
4.2 Point source maximum emission rates (normal operating conditions) ................................. 18
4.3 Point source maximum emission rates (start-up, shut-down, upset and maintenance
conditions) ......................................................................................................................................... 19
4.4 Fugitive emissions ................................................................................................................. 20
4.5 Emergency Incidents ............................................................................................................. 20
5. Impact of Enterprise on the Receiving Environment .............................................................. 21
5.1 Analysis of emissions ............................................................................................................ 21
5.1.1 Overview ....................................................................................................................... 21
5.1.2 Prevailing climatic conditions ........................................................................................ 21
5.2 Current status of ambient air quality ..................................................................................... 23
5.2.1 Ambient air quality monitoring ....................................................................................... 23
5.2.2 Source apportionment ................................................................................................... 32
v
5.3 Dispersion modelling ............................................................................................................. 33
5.3.1 Models used .................................................................................................................. 33
5.3.2 Model parameterisation ................................................................................................. 34
5.3.3 Model accuracy ............................................................................................................. 36
5.4 Modelled ambient concentrations ......................................................................................... 38
5.4.1 Modelled operational scenarios .................................................................................... 38
5.4.2 Scenario 1: Current actual emissions ........................................................................... 39
5.4.3 Scenario 2: Requested emission limits ......................................................................... 44
5.5 Modelled cumulative ambient concentrations for the Northern Highveld.............................. 49
5.5.1 Modelled operational scenarios .................................................................................... 49
5.5.2 Scenario 1: Current actual emissions ........................................................................... 49
5.5.3 Scenario 2: Requested emission limits ......................................................................... 54
5.6 Analysis of Emissions’ Impact on Human Health .................................................................. 61
5.6.1 Potential health effects .................................................................................................. 61
5.6.2 Analysis ......................................................................................................................... 62
5.7 Analysis of Emissions’ Impact on the Environment .............................................................. 63
6. Complaints ................................................................................................................................... 65
7. Current or planned air quality management interventions ..................................................... 65
8. Compliance and Enforcement History ...................................................................................... 65
9. Additional Information ................................................................................................................ 65
10. Summary and conclusion ........................................................................................................... 66
11. References ................................................................................................................................... 68
12. Formal Declarations .................................................................................................................... 69
vi
TABLES
Table 1: Enterprise details ...................................................................................................................... 9
Table 2: Site information ....................................................................................................................... 10
Table 3: Current government authorisations related to air quality ........................................................ 12
Table 4: Minimum Emission Standards for combustion installations (Category 1) using solid fuel for
electricity generation (Sub-category 1.1) with a design capacity equal or greater to 50 MW
heat input per unit ............................................................................................................... 12
Table 5: National Ambient Air Quality Standards for SO2, NO2 and PM10 (DEA, 2009) and PM2.5 (DEA,
2012a). Because the applications apply to regulations that commence in 2015, the 2015
and 2016 standards are deemed to apply. ......................................................................... 13
Table 6: Activities listed in GN 893 which are ‘triggered’ by the Kriel Power Station. .......................... 14
Table 7: Unit processes at Kriel Power Station..................................................................................... 16
Table 8: Raw material used at Kriel Power Station .............................................................................. 17
Table 9: Production rates at Kriel Power Station .................................................................................. 17
Table 10: Energy sources used at Kriel Power Station ........................................................................ 17
Table 11 : Appliance and abatement equipment control technology currently used at Kriel Power
Station. ................................................................................................................................ 17
Table 12: Point sources at Kriel Power Station..................................................................................... 18
Table 13: Maximum permitted emission rate of pollutants under normal operating conditions at Kriel
Power Station ..................................................................................................................... 18
Table 14: Start-ups at Kriel Power Station for the period 2010 to 2013. .............................................. 19
Table 15: Upset Conditions experienced at Kriel Power Station .......................................................... 20
Table 16: Ambient hourly average concentrations of SO2 for the 99th percentile (in μg/m3), together with
the percentile at which the limit value was reached for the three monitoring years, at Kriel,
Elandsfontein, and Komati monitoring stations. ................................................................. 24
Table 17: Parameterisation of key variables for CALMET .................................................................... 35
Table 18: Parameterisation of key variables for CALPUFF .................................................................. 36
Table 19: Comparison between measured and modelled concentrations for those power stations where
a reasonable correlation between the two can be expected. The range derives from the
three-year monitoring period where the best and worst correlation of the three years is
presented. ........................................................................................................................... 37
Table 20: Current average emissions (tons/annum) and Eskom requested emission limits (mg/Nm3) for
Kriel Power Station ............................................................................................................. 38
Table 21: Predicted annual average concentration and the 99th percentile concentration at the points of
maximum ground-level impact for the Actual Current Emissions and Requested Emission
Limits. ................................................................................................................................. 39
Table 22: Predicted annual average concentration and the 99th percentile concentration at the points
of maximum ground-level impact for the Actual Current Emissions and Requested Emission
Limits .................................................................................................................................. 49
Table 23: Complaints register for Kriel Power Station .......................................................................... 65
FIGURES
Figure 1: Relative location of the Kriel Power Station (Google Earth, 2013) ........................................ 10
Figure 2: Land-use and sensitive receptors within a 30x30 km block of the Kriel Power Station (shown
by the white square) ........................................................................................................... 11
vii
Figure 3: A basic atmospheric emissions mass balance for Kriel Power Station showing the key inputs
and outputs. Note that all quantities are expressed in tonnes per annum unless otherwise
stated. ................................................................................................................................. 15
Figure 4: Relative location of the different process units at Kriel Power Station ................................. 16
Figure 5: Average monthly maximum and minimum temperature, and average monthly rainfall at Loskop
Dam from 1961 to 1990 ...................................................................................................... 22
Figure 6: Annual windrose for Kriel Village 2010 to 2012 ..................................................................... 22
Figure 7: Frequency distribution of ten-minute average ambient SO2 concentrations measured at the
Kriel Village monitoring station from 2011 to 2012. The NAAQS limit value of 500 μg/m3 is
shown by the red horizontal line. ........................................................................................ 24
Figure 8: Frequency distribution of hourly average ambient SO2 concentrations measured at the Kriel
Village (a.), Elandsfontein (b.), and Komati (c.) monitoring stations from 2010 to 2012. The
NAAQS limit value of 350 μg/m3 is shown by the red horizontal line. ................................ 25
Figure 9: Frequency distribution of daily (24-hour) average ambient SO2 concentrations measured at
the Kriel Village (a.), Elandsfontein (b.), and Komati (c.) monitoring stations from 2010 to
2012. The NAAQS limit value of 125 μg/m3 is shown by the red horizontal line. ............... 27
Figure 10: Frequency distribution of daily average ambient PM10 concentrations measured at the Kriel
Village (a.), Elandsfontein (b.), and Komati (c.) monitoring stations from 2010 to 2012. The
2015 NAAQS limit value of 75 μg/m3 is shown by the red horizontal line. ......................... 29
Figure 11: Frequency distribution of hourly average ambient NO2 concentrations measured at the Kriel
Village (a.), Elandsfontein (b.), and Komati (c.) monitoring stations from 2010 to 2012. The
NAAQS limit value of 200 μg/m3 is shown by the red horizontal line. ................................ 31
Figure 12: Average hourly SO2, NO2 and PM10 concentrations for June at Kriel Village calculated over
the period 2010 to 2013 ...................................................................................................... 32
Figure 13: TAPM and CALPUFF modelling domains for Kriel, showing the relative locations of the
meteorological stations ....................................................................................................... 35
Figure 14: Annual average SO2 concentrations (µg/m3) resulting from actual emissions from Kriel Power
Station emissions (Scenario 1) ........................................................................................... 40
Figure 15: Predicted 99th percentile 24-hour average SO2 concentrations (µg/m3) resulting from actual
emissions from Kriel Power Station (Scenario 1) ............................................................... 40
Figure 16: Predicted 99th percentile hourly SO2 concentrations (µg/m3) resulting from actual emissions
from Kriel Power Station (Scenario 1) ............................................................................... 41
Figure 17: Annual average PM10 concentrations (µg/m3) resulting from actual emissions from Kriel
Power Station (Scenario 1) ................................................................................................ 42
Figure 18: Predicted 99th percentile 24-hour PM10 concentrations (µg/m3) resulting from actual
emissions from Kriel Power Station (Scenario 1) .............................................................. 42
Figure 19: Annual average NO2 concentrations (µg/m3) resulting from actual emissions from Kriel
Power Station (Scenario 1) ................................................................................................ 43
Figure 20: 99th percentile concentration of the predicted maximum hourly NO2 concentrations (µg/m3)
resulting from actual emissions from Kriel Power Station (Scenario 1) ............................. 43
Figure 21: Annual average SO2 concentrations (µg/m3) resulting from Eskom’s requested emission limit
for Kriel Power Station (Scenario 2) ................................................................................... 44
Figure 22: Predicted 99th percentile 24-hour SO2 concentrations (µg/m3) resulting from Eskom’s
requested emission limit for Kriel Power Station (Scenario 2) ........................................... 45
Figure 23: Predicted 99th percentile hourly SO2 concentrations (µg/m3) resulting from the requested
emission limit for Kriel Power Station (Scenario 2) ............................................................ 45
Figure 24: Annual average PM10 concentrations (µg/m3) resulting from Eskom’s requested emission
limits for Kriel Power Station (Scenario 2) .......................................................................... 46
Figure 25: Predicted 99th percentile 24-hour PM10 concentrations (µg/m3) resulting from Eskom’s
requested emission limits for Kriel Power Station (Scenario 2) ......................................... 47
viii
Figure 26: Annual average NO2 concentrations (µg/m3) resulting from Eskom’s requested emission
limits for Kriel Power Station (Scenario 2) ......................................................................... 48
Figure 27: 99th percentile concentration of the predicted maximum hourly NO2 concentrations (µg/m3)
resulting from Eskom’s requested emission limits for Kriel Power Station (Scenario 2a) . 48
Figure 28: SO2 Scenario 1 – Predicted annual average SO2 concentrations (µg/m3) resulting from
current emissions from Northern Highveld power stations (combined) .............................. 50
Figure 29: SO2 Scenario 1 – 99th percentile concentration of the predicted 24-hour SO2 concentrations
(µg/m3) for current emissions from Northern Highveld power stations (combined)............ 50
Figure 30: SO2 Scenario 1 – 99th percentile of the predicted 1-hour SO2 concentrations (µg/m3) resulting
from current actual emissions from Northern Highveld power stations (combined) ........... 51
Figure 31: NO2 Scenario 1 – Predicted annual average NO2 concentrations (µg/m3) resulting from
current actual emissions from Northern Highveld power stations (combined) ................... 52
Figure 32: NO2 Scenario 1 – 99th percentile of the predicted 1-hour NO2 concentrations (µg/m3) resulting
from current actual emissions from Northern Highveld power stations (combined) ........... 52
Figure 33: PM10 Scenario 1 – Predicted annual average PM10 concentrations (µg/m3) resulting from
actual emission limits from Northern Highveld power stations (combined) ........................ 53
Figure 34: PM10 Scenario 1 – 99th percentile of the predicted 24-hour PM10 concentrations (µg/m3)
resulting from actual emission limits from Northern Highveld power stations (combined) . 54
Figure 35: SO2 Scenario 2 – Predicted annual average SO2 concentrations (µg/m3) resulting from
requested emissions limits from Northern Highveld power stations (combined)................ 55
Figure 36: SO2 Scenario 2 – 99th percentile concentration (µg/m3 ) of the predicted 24-hour SO2
concentrations for requested emissions from Northern Highveld power stations (combined)
[red line = NAAQS limit value] ............................................................................................ 55
Figure 37: SO2 Scenario 2 – 99th percentile of the predicted 1-hour SO2 concentrations (µg/m3) resulting
from requested emission from Northern Highveld power stations (combined) [red line =
NAAQS limit value] ............................................................................................................. 56
Figure 38: SO2 Scenario 2 – 99th percentile of the predicted 24-hour SO2 concentrations (µg/m3) –
Number of exceedances of the NAAQS limit value [within the boundary of the red line] .. 56
Figure 39: SO2 Scenario 2 – 99th percentile of the predicted 1-hour SO2 concentrations (µg/m3) –
Number of exceedances of the NAAQS limit value[within the boundary of the red line] ... 57
Figure 40: NO2 Scenario 2 – Predicted annual average NO2 concentrations (µg/m3) resulting from
requested emission limits from Northern Highveld power stations (combined) ................. 58
Figure 41: NO2 Scenario 2 – 99th percentile of the predicted 1-hour NO2 concentrations (µg/m3) resulting
from requested emission limits from Northern Highveld power stations (combined) ......... 58
Figure 42: NO2 Scenario 2 – 99th percentile of the predicted 1-hour NO2 concentrations (µg/m3) [white
squares represent areas of marginal non-compliance with NAAQS) ................................. 59
Figure 43: PM10 Scenario 2 – Predicted annual average PM10 concentrations (µg/m3) resulting from
requested emission limits from Northern Highveld power stations (combined) ................. 60
Figure 44: PM10 Scenario 2 – 99th percentile of the predicted 24-hour PM10 concentrations (µg/m3)
resulting from requested emission limits from Northern Highveld power stations (combined)
............................................................................................................................................ 60
1. Enterprise Details
1.1 Enterprise Details
Entity details for Eskom’s Kriel Power Station are listed in Table 1.
Table 1: Enterprise details
Entity Name: Eskom Holdings SOC Limited
Trading as: Kriel Power Station
Type of Enterprise, e.g. Company/Close
Corporation/Trust, etc.: State owned company
Company/Close Corporation/Trust
Registration Number (Registration
Numbers if Joint Venture):
2002/015527/06
Registered Address: Megawatt Park, Maxwell Drive, Sunninghill, Sandton
Postal Address: Private Bag X7272, Witbank, 1035
Telephone Number (General): 013 647 9111
Fax Number (General): 013 647 6904
Company Website: www.eskom.co.za
Industry Type/Nature of Trade:
Coal-fired power stations that generate electricity.
Listed activity (Sub-category 1.1) in terms of the NEMAQA (Section 21),
i.e. combustion installations using solid fuels (excluding biomass)
primarily for steam raising or electricity generation (DEA, 2013).
Land Use Zoning as per Town Planning
Scheme: Agricultural/Heavy industry
Land Use Rights if outside Town Planning
Scheme: -
Responsible Person: Thomas Conradie
Emissions Control Officer: Thomas Conradie
Telephone Number: 017 615 2571
Cell Phone Number: 082 325 6109
Fax Number: 086 668 1195
Email Address: [email protected]
After Hours Contact Details: 082 325 6109
10
1.2 Location and extent of the Plant
Kriel Power Station is located in the Mpumalanga Province, approximately 7.5 km west of the town of
Kriel. The surrounding land use is zoned as agricultural, comprising low density farmsteads and
infrastructure, crops on the arable soils and grazing. It borders the Matla Power Station and the Matla
Mine (Exxaro). Site information is provided in Table 2 and the relative location to key landmarks is
shown in Figure 1.
Figure 1: Relative location of the Kriel Power Station (Google Earth, 2013)
Table 2: Site information
Physical Address of the Plant (Licensed Premises): Kriel Power Station, Ogies Bethal Road 15 km from
Kriel Town
Description of Site (Where No Street Address): On Ogies Bethal Road, 15 km from Kriel Town
Coordinates (latitude, longitude) of Approximate Centre of
Operations (Decimal Degrees):
Latitude: 26.25 oS
Longitude: 29.17 oE
Coordinates (UTM) of Approximate Centre of Operations: 717 710 E
7 093 588 S
Extent (km²): 60.991
Elevation Above Mean Sea Level (m) 1 624
Province: Mpumalanga Province
District/Metropolitan Municipality: Nkangala District Municipality
Local Municipality: Emalahleni Local Municipality
Designated Priority Area (if applicable): Highveld Priority Area
11
Receptor Distance(km) Direction
Kriel 7.5 E
Thubelihle 11.5 ENE
Residential area 9.4 NNE
Agricultural lands Immediate Surrounding
Kriel 7.5 E
Figure 2: Land-use and sensitive receptors within a 30x30 km block of the Kriel Power
Station (shown by the white square)
1.3 Atmospheric Emission License and Other Authorisations
An Atmospheric Emission License (AEL) (No. 17/4/AEL/MP312/11/09) was issued to Kriel Power
Station by the Mpumulanga MEC on 6 June 2013, in terms of Section 47(1) of the National
Environmental Management: Air Quality Act, 2004 (Act No. 39 of 2004) (NEMAQA) in respect of
Schedule Process No.29 (Power Generation) and Schedule Process No. 59 (Bulk Storage and
Handling of Ore or Coal). An amended AEL was issued on 10 September 2013. The AEL is valid until
20 May 2017 and replaces the APPA Registration Certificate.
The AEL specifies permissible stack emission concentrations for Particulate Matter, Sulphur dioxide
(SO2) and oxides of Nitrogen (NOX). It also specifies a number of compliance conditions as well as
conditions for emission monitoring, management of abnormal releases and management of fugitive
dust resulting from coal handling and storage.
12
Table 3: Current government authorisations related to air quality
NEMAQA Registration
Certificate Number:
Date of
Registration
Certificate:
Listed Activity
Number/ Category
Number:
Listed Activity Description:
17/4/AEL/MP312/11/09 06/06/2013
Category 1
Sub-category 1.1
Solid fuels (excluding biomass) combustion
installations used primarily for steam raising or
electricity generation.
Category 2
Sub-category 2.2
Petroleum product storage tanks and product
transfer facilities, except those used for liquefied
petroleum gas.
Category 5
Sub-category 5.1
Storage and handling of ore and coal not situated on
the premises a mine or work as defined in the mines
Health and Safety Act 29/1996
1.3.1 Minimum Emission Standards
In terms of NEMAQA, all of Eskom's coal- and liquid fuel-fired power stations are required to meet the
Minimum Emission Standards (MES) contained in GNR 893 on 22 November 2013 ("GNR 893")
promulgated in terms of Section 21 of the NEMAQA. GNR 893 does provide for transitional
arrangements in respect of the requirement for existing plants to meet the MES and provides that less
stringent limits must be achieved by existing plants by 1 April 2015, and the more stringent ‘new plant’
limits must be achieved by existing plants by 1 April 2020. The MES are listed in Table 4.
Table 4: Minimum Emission Standards for combustion installations (Category 1) using
solid fuel for electricity generation (Sub-category 1.1) with a design capacity equal or
greater to 50 MW heat input per unit
Substance Plant status MES mg/Nm3 under normal conditions of 10%
O2, 273 K and 101.3 kPa
Particulate New 50
Existing 100
Sulphur dioxide New 500
Existing 3 500
Oxides of nitrogen New 750
Existing 1 100
1.3.2 National Ambient Air Quality Standards (NAAQS)
The effects of air pollutants on human health occur in a number of ways with short-term, or acute
effects, and chronic, or long-term, effects. Different groups of people are affected differently,
depending on their level of sensitivity, with the elderly and young children being more susceptible.
Factors that link the concentration of an air pollutant to an observed health effect are the concentration
and the duration of the exposure to that particular air pollutant.
Criteria pollutants occur ubiquitously in urban and industrial environments. Their effects on human
health and the environment are well documented (e.g. WHO, 1999; 2003; 2005). South Africa has
accordingly established National Ambient Air Quality Standards (NAAQS) for the criteria pollutants, i.e.
sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), respirable particulate matter
(PM10), ozone (O3), lead (Pb) and benzene (C6H6) (DEA, 2009) and PM2.5 (DEA, 2012a). The NAAQS
for SO2, NO2, PM10 and PM2.5 are listed in Table 5.
13
The NAAQS consists of a ‘limit’ value and a permitted frequency of exceedance. The limit value is the
fixed concentration level aimed at reducing the harmful effects of a pollutant. The permitted frequency
of exceedance represents the acceptable number of exceedances of the limit value expressed as the
99th percentile. Compliance with the ambient standard implies that the frequency of exceedance of the
limit value does not exceed the permitted tolerance. Being a health-based standard, ambient
concentrations below the standard imply that air quality poses an acceptable risk to human health,
while exposure to ambient concentrations above the standard implies that there is an unacceptable
risk to human health.
Table 5: National Ambient Air Quality Standards for SO2, NO2 and PM10 (DEA, 2009) and
PM2.5 (DEA, 2012a). Because the applications apply to regulations that commence in
2015, the 2015 and 2016 standards are deemed to apply.
Pollutants Averaging period Limit value (µg/m3) Number of permissible exceedances
per annum
SO2
1 hour 350 88
24 hour 125 4
1 year 50 0
NO2 1 hour 200 88
1 year 40 0
PM10 24-hour 120 (751) 4
Calendar year 50 (401) 0
PM2.5 24-hour 65 (402) (253) 4
Calendar year 25 (202) (153) 0
1: Implementation date 1 January 2015
2: Implementation date 1 January 2016
3: Implementation date 1 January 2030
14
2. Nature of the Process
2.1 Listed Activity or Activities
Table 6: Activities listed in GN 893 which are ‘triggered’ by the Kriel Power Station.
Category of Listed Activity Sub-category of the
Listed Activity Description of the Listed Activity
1: Combustion Installations 1.1: Solid Fuel
Combustion Installations
Solid fuels combustion installations used primarily for
steam raising or electricity generation.
All installations with design capacity equal to or greater
than 50 MW heat input per unit, based on the lower
calorific value of the fuel used.
2: Petroleum Industry, the
production of gaseous and
liquid fuels as well as
petrochemicals from crude oil,
coal, gas or biomass
2.4: Storage and Handling
of Petroleum Products
All permanent immobile liquid storage facilities at a single
site with a combined storage capacity of greater than 1000
cubic meters.
5: Mineral Processing, Storage
and Handling
5.1 Storage and Handling
of Ore and Coal
Storage and handling of ore and coal not situated on the
premises of a mine or works as defined in the Mines Health
and Safety Act 29/1996.
2.2 Process Description
Eskom Holdings SOC Limited is a South African utility that generates, transmits and distributes
electricity. The bulk of that electricity is generated by large coal-fired power stations that are situated
close to the sources of coal, with most of the stations occurring on the Mpumalanga Highveld. The Kriel
Power Station (hereafter referred to as ‘Kriel’) is one such station (Figure 1). Kriel has total installed
capacity of 3 000 MW, with an installed capacity of 500MW per unit.
At Kriel, and indeed all the coal-fired power stations, pulverised coal is combusted in order to heat
water in boilers to generate steam at high temperatures (between 500°C and 535°C) and pressures.
The steam, in turn, is used to drive the turbines, which are connected, to rotating magnets and
electricity is generated. The energy in the fuel (coal) is thus converted to electricity (Figure 3).
15
Figure 3: A basic atmospheric emissions mass balance for Kriel Power Station
showing the key inputs and outputs. Note that all quantities are expressed in tonnes
per annum unless otherwise stated.
Kriel Power Station receives approximately 10 million tons of coal from the mine per annum. The coal
is conveyed from the mine to the coal stockyard on site where it is milled to pulverised fuel and fed to
the six boilers. Combustion of the coal in the boilers heats water to superheated steam, which drives
the turbines. In turn, the turbines drive the generators which generate 3 000 MW of electricity. A
detailed description of the process is contained in the assessment of technology options for Eskom’s
coal fired power stations (Appendix B).
2.2.1 Atmospheric emissions resulting from power generation
Atmospheric emissions depend on the fuel composition and rate of consumption, boiler design and
operation, and the efficacy of pollution control devices. Emissions from Kriel include sulphur dioxide
(SO2), oxides of nitrogen (NO + NO2 = NOX) and Particulate Matter (PM).
SO2 is produced from the combustion of sulphur bound in coal. The stoichiometric ratio of SO2 to
sulphur dictates that 2 kg of SO2 are produced from every kilogram of sulphur combusted. The coal
used by the Kriel Power Station has a sulphur content (wt %) of 0.6 – 0.8 %. NOX is produced from
thermal fixation of atmospheric nitrogen in the combustion flame and from oxidation of nitrogen bound
in the coal. The quantity of NOX produced is directly proportional to the temperature of the flame.
The non-combustible portion of the fuel remains as solid waste. The coarser, heavier waste is called
‘bottom ash’ and is extracted from the boiler, and the lighter, finer portion is ‘fly ash’ and is usually
suspended in the flue gas, and in the absence of any emission control would be emitted as PM through
the stack. The coal used at Kriel has an ash content of between 24 and 27%.
Emissions abatement
Boilers 1-6
Turbines and generators
Ash disposal Coal mine
Coal stockyard
Coal mill
CO2
17.5 Mtons/
annum
SO2
136 413 tons/
annum
NOx
101 628 tons/
annum
PM
16 638 tons/
annum
Electricity
16 571 GWh SO
Ash
2.46 Mtons/
annum
Coal 8.90 Mtons/annum
Fuel oil 21 124 tons/
annum
Figures based on 2012/2013 financial year Coal figures include mill discards, and are based on coal that is moved from the stockyard to the mill
16
2.3 Unit Processes
A summary of the different unit process is provided in Table 7. The relative location of these is shown
in Figure 4.
Table 7: Unit processes at Kriel Power Station
Unit Process Function of Unit Process Batch or Continuous Process
Boiler Unit 1 Generation of electricity from coal Continuous
Boiler Unit 2 Generation of electricity from coal Continuous
Boiler Unit 3 Generation of electricity from coal Continuous
Boiler Unit 4 Generation of electricity from coal Continuous
Boiler Unit 5 Generation of electricity from coal Continuous
Boiler Unit 6 Generation of electricity from coal Continuous
Coal stockpile Storage of coal Continuous
Fuel oil storage tanks Storage of fuel oil Continuous
Figure 4: Relative location of the different process units at Kriel Power Station
Boilers 1 - 6
17
3. Technical Information
3.1 Raw Materials Used
The permitted raw materials consumption rate, the permitted production rates and the energy sources
at Kriel Power Station are listed in Tables 8 to 10 according to the AEL.
Table 8: Raw material used at Kriel Power Station
Raw material Maximum permitted consumption rate (Volume) Units (quantity / period)
Coal 1 227 600 tons/month
Fuel oil 5 000 tons/month
Table 9: Production rates at Kriel Power Station
Product/by-product Maximum Production capacity permitted (Volume) Units
(quantity / period)
Electricity 3 600 MW
Table 10: Energy sources used at Kriel Power Station
Energy
source
Sulphur content
of fuel (%)
Ash content
of fuel (%)
CV
(MJ/kg)
Maximum permitted
consumption rate (Volume)
Units
(quantity / period)
Coal 0.6 to 1.2% 27 to 32 % 18-24 1 227 600 tons/month
Fuel oil 5 000 tons/month
3.2 Appliances and Abatement Equipment Control Technology
Abatement equipment control technology at Kriel is presented in Table 11. It should be noted that the
abatement equipment is only for the control of PM emissions. Neither NOx nor SO2 emissions are
controlled directly at the power station.
Table 11 : Appliance and abatement equipment control technology currently used at Kriel Power Station.
Appliance Name Appliance Type /
Description Appliance Function / Purpose
Electrostatic Precipitators (ESPs) Electrostatic
Precipitator (ESPs)
An ESP removes particles from the flue stream using the
force of an induced electrostatic charge on the ash particle
that is then attracted to and held on a plate. The efficiency
of ESPs is dependent on the electrical resistivity of the ash
particles (and the particle size). SO3 injection decreases
the resistivity of the particles, and significantly improves
the performance of the ESP. SO3 Plant (i.e. flue gas
conditioning plant) SO3 Injection
4. Atmospheric emissions
4.1 Point source parameters
The physical data for the stacks at Kriel Power Station are listed in Table 12. Emission concentrations and emission rates for current production and proposed
operational levels are shown in Table 13. The boiler units operate continuously, i.e. 24 hours a day.
Table 12: Point sources at Kriel Power Station
Point
Source
Code
Source name
Latitude
(UTM)
(m)
Longitude
(UTM)
(m)
Height of
Release Above
Ground (m)
Height above
nearby
building (m)
Diameter at
Stack Tip /
Vent Exit (m)
Actual Gas
Exit Temp
(0C)
Actual gas
volumetric
flow (m3/hr)
Actual Gas
Exit Velocity
(m/s)
Type of emission
(continuous/
batch)
Stack 1
Boiler unit 1
717541 E 7094489 S 213 79.2 14.3* 130 10 800 000 17 Continuous Boiler unit 2
Boiler unit 3
Stack 2
Boiler unit 4
717658 E 70914286 S 213 79.2 14.3* 130 10 800 000 17 Continuous Boiler unit 5
Boiler unit 6
*Effective diameter of combined stack, each flue is 7.2m in diameter.
4.2 Point source maximum emission rates (normal operating conditions)
Table 13: Maximum permitted emission rate of pollutants under normal operating conditions at Kriel Power Station
Point source
number
Point source name (as in
paragraph 4.1. above) Pollutant name
Maximum emission rate Duration of emissions
(mg/Nm3) Averaging period
Stack 1 & 2 Boiler units 1-6
SO2
Immediately: 4000
1 April 2015: 3500
2020; 500
24 hours Continuous
NOx
Immediately: 1700
1 April 2015: 1100
2020; 750
24 hours Continuous
PM
Immediately: 125
1 April 2015: 100
2020:
24 hours Continuous
4.3 Point source maximum emission rates (start-up, shut-down, upset
and maintenance conditions)
Kriel Power Station maintains a record of all start-ups that occur, as well as the type of start-
up. Full details of these for the years 2010 – 2013 are provided in Table 14.
Table 14: Start-ups at Kriel Power Station for the period 2010 to 2013.
Month
Number
of
Start-
ups
Type
of
Start-
up
Month
Number
of
Start-
ups
Type
of
Start-
up
Month
Number
of Start-
ups
Type
of
Start-
up
Month
Number
of
Start-
ups
Type
of
Start-
up
2010 2011 2012 2013
April 1 Hot January 1 Warm January 1 Hot January 1 Warm
April 2 Cold January 3 Hot January 1 Cold January 2 Cold
May 1 Cold January 3 Cold January 2 Warm February 1 Hot
May 2 Warm February 1 Hot February 1 Hot February 5 Cold
May 3 Hot February 5 Cold February 5 Cold February 2 Warm
June 3 Warm March 2 Warm March 3 Cold March 3 Hot
June 7 Cold March 2 Cold March 2 Hot March 6 Cold
June 4 Hot April 1 Warm March 4 Warm March 1 Warm
July 2 Warm April 1 Cold April 1 Hot April 4 Cold
July 7 Hot April 2 Hot April 1 Warm April 3 Hot
July 9 Cold May 4 Cold May 1 Warm April 1 Warm
August 3 Warm May 1 Hot May 5 Cold May 2 Hot
August 2 Hot June 2 Cold May 1 Hot May 2 Cold
August 2 Cold June 1 Hot June 2 Warm May 1 Warm
September 4 Cold July 3 Cold June 6 Cold June 5 Cold
September 1 Hot July 1 Warm July 1 Cold June 3 Warm
September 1 Warm July 3 Hot July 2 Warm July 1 Cold
October 4 Hot August 1 Warm August 2 Hot July 1 Hot
October 2 Warm August 3 Cold August 1 Warm August 2 Cold
October 8 Cold August 1 Hot August 2 Cold August 1 Warm
November 2 Warm September 1 Hot September 2 Warm August 3 Hot
November 4 Cold September 1 Cold September 5 Cold September 1 Hot
November 1 Hot September 1 Warm September 2 Hot September 4 Warm
December 2 Hot October 4 Cold October 4 Cold September 6 Cold
December 3 Warm November 3 Warm October 2 Warm
December 5 Cold November 3 Cold November 3 Warm
December 3 Warm November 2 Hot
December 1 Cold November 3 Cold
December 3 Cold
December 2 Warm
December 2 Hot
A hot start follows an off-load period of less than 8 hours.
A warm start follows an off-load period of between 8 and 30 hours.
A cold start follows an off-load period of more than 30 hours.
A record is maintained of all upset conditions which the power station experiences. Details of
these are provided in Table 15.
20
Table 15: Upset Conditions experienced at Kriel Power Station
Station Date of event Description
Kriel Units 1 - 6 April 1 – 30 2013 Poor electrical performance of precipitator fields.
Kriel Units 1-6 April 1 – 30 2013 Poor electrical performance of precipitator fields.
Kriel Units 1- 6 August 1 – 31 2013
North Stack (Unit 1-3) The convertor vessel inlet and outlet
temperatures were not performing to the design specifications; Full
dust hoppers; Some rapping gear drives are not working. South
Stack (Unit 4-6) Full dust hoppers; Problems experienced with ESPs
on Units 4 and 5. Dust Handling Plant problems on units 4 and 6.
Kriel Units 1-6 July 1 – 31 2013
Poor electrical precipitator performance on the North Stack. Holes
in ducting and ESPs on both stacks. Unit 5 experiencing condenser
problems.
Kriel Units 1-6 June 1 – 30 2013
The persistence of the moisture/air ingress into the ducts and
precipitator casings results in poor performance of the precips on
Units 1 -3. Units 4 -6 have a high number of failed drives for DE and
CE.
Kriel Units 1-6 May 1-31 2013 Problems are experienced with moisture and air ingress
4.4 Fugitive emissions
Fugitive emissions at Kriel Power Station result from coal storage and handling, and ashing
activities. The AEL requires a fugitive dust management plan, but emission limits do not apply.
Fugitive emissions are not assessed in this AIR.
See the power station’s fugitive emission management plan included as Annexure G for a
description of fugitive emission sources and measures that have been put in place to manage
them. Fugitive emissions are extremely difficult to quantify, as they are highly variable in time
and space. Fugitive emissions from the ashing facility are highest on the active face (especially
in the case of dry ashing) and when wind speeds are high. Fugitive emissions also depend on
measures that have been put in place to suppress dust generation, for example vegetation of
the ashing facility and sprinklers to suppress dust. The dust fall-out resulting from the fugitive
emissions will be monitored with dust buckets.
4.5 Emergency Incidents
A record is maintained of all emergency incidents occurring at Eskom Power Stations reported
in terms of Section 30 of the National Environmental Management Act, 1998
(Act No. 107 of 1998) (NEMA). Kriel Power Station is unable to consistently comply with the
particulate emission limits in the AEL, and this has been reported in terms of Section 30 of
NEMA.
21
5. Impact of Enterprise on the Receiving Environment
5.1 Analysis of emissions
5.1.1 Overview
The application for postponement means that Kriel’s emissions will remain unchanged from
what they are currently. In addition the requested interim emissions have been expressed as
a ceiling limit to ensure that Eskom can comply with the same under all normal operating
circumstances given the variability of emissions from day to day. As such, assessing the impact
of Kriel on the receiving environment requires that:
The existing state of the environment must be assessed in terms of prevailing climate
and air quality, including those areas where there are no direct measurements of air
quality;
The air quality that could prevail if the ceiling limits are approved must also be
assessed; and,
The air quality state must then be assessed in terms of the risks to human health and
the environment.
This assessment is then based on a detailed analysis of the prevailing climate together with an
analysis of air quality monitoring data. Thereafter dispersion modelling is used to predict
ambient air pollution concentrations in the areas where there are no physical measurements
for worst case scenario under the requested interim PM and SO2 emissions. This analysis is
presented in the following section.
5.1.2 Prevailing climatic conditions
Temperature and rainfall
The climate of a location is affected by its latitude, terrain, and altitude, as well as nearby water
bodies and their currents. Climates can be classified according to the average and the typical
ranges of different variables, most commonly temperature and precipitation.
The Mpumalanga Highveld is located in temperate latitudes between 25 and 26º S and 28 to
29º E, and approximately 1 600 m above sea level. As a result, it experiences a temperate
climate with summer rainfall and dry winters according to the Köppen Climate Classification
system. The Mpumalanga Highveld is relatively flat and experiences similar climate throughout.
Temperature and rainfall for north-eastern parts of the Mpumalanga Highveld are therefore best
illustrated by the long term measurements at the South African Weather Service station at the
Loskop Dam (Figure 5).
Winters are mild and dry with average maximum temperatures dropping below 25 °C in May,
June, July, and August but cold at night in June and July when temperatures drop below 7 °C.
Average summer maximums exceed 27 °C from September to March, with extremes reaching
more than 30 °C particularly from December to January.
The area experienced an annual average rainfall of 640 mm with rain occurring almost
exclusively in the summer months from October to March, with more than 60% of the rain
occurring from November to February (Figure 5). Rainfall seldom occurs in winter between
April and September.
22
Figure 5: Average monthly maximum and minimum temperature, and average
monthly rainfall at Loskop Dam from 1961 to 1990
Wind
The Mpumalanga Highveld is relatively flat with little influence by topography on the wind flow.
Winds at Kriel are best represented by the wind measured at Eskom’s monitoring station at
Kriel Village, 7km east of the power station.
The windrose in Figure 6 illustrates the frequency of hourly wind from the 16 cardinal wind
directions, with wind indicated from the direction it blows, i.e. easterly winds blow from the east.
It also illustrates the frequency of average hourly wind speed in six wind speed classes.
The winds are predominantly northerly and north-westerly winds (Figure 6). Occasional
easterly winds occur and are associated with the relative location and strength of the Indian
Ocean anticyclone. The winds are generally light with 40% of all winds less than 3 m/s and
60% of all winds less than 6 m/s.
Figure 6: Annual windrose for Kriel Village 2010 to 2012
0
20
40
60
80
100
120
140
160
0
5
10
15
20
25
30
35
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Average m
onth
ly rain
fall
(m
m)
Tem
peratu
re (⁰C
)
Mean maximum temperature Mean minimum temperature Average monthly rainfall
23
5.2 Current status of ambient air quality
The rich coal and mineral reserves in the Mpumalanga Highveld area have led to the
establishment of the power generation hub including, amongst others, the Kriel, Matla, Kendal,
Hendrina and Arnot Power Stations and the construction of the Kusile Power Station. It also
houses considerable coal mining activities, ferrometal processing plants, and other major
industry. Other sources of air pollution on the Mpumalanga Highveld include the domestic
burning of coal, agricultural activities and motor vehicle emissions. A comprehensive
description of sources of air pollution on the Highveld is continued in the Air Quality
Management Plan for the Highveld priority Area (DEA, 2012a). This section provides a
summary of air quality pertinent to the Kriel Power Station.
5.2.1 Ambient air quality monitoring
Eskom established an ambient air quality monitoring station at Kriel Village, 7 km east of Kriel
Power Station, measuring, amongst others, ambient SO2, NO2 and PM10 concentrations and
meteorological parameters. The monitoring station is situated in the zone of maximum ground-
level impact, and as such indicates the highest concentrations that can be expected anywhere
in the vicinity of Kriel Power Station. Eskom also established ambient air quality monitoring
stations at Elandsfontein, and Komati.
Ambient data for the three year period 2010, 2011 and 2012 at the monitoring stations provide
some indication of ambient air quality in the area and of the sources that influence air quality at
the site. The data are presented in frequency distributions that serve to indicate the frequency
of different concentrations measured.
Sulphur dioxide (SO2)
Ten-minute average SO2 concentrations measured at Kriel Village monitoring station are shown
in Figure 7. It can be seen from the frequency distribution that the ten-minute limit value is
exceeded but for less than the 1% frequency for which exceedances of the limit value are
allowed. No data is available for 2010 but the 99th percentile values are 261 and 262 μg/m3 for
2011 and 2012, respectively. There is thus compliance with the 10-minute NAAQS for SO2.
(10-minute data is not recorded yet at the Elandsfontein and Komati monitoring stations).
24
Figure 7: Frequency distribution of ten-minute average ambient SO2 concentrations measured at the Kriel Village monitoring station from 2011 to 2012. The NAAQS limit value of 500 μg/m 3 is shown by the red horizontal line.
Hourly average SO2 concentrations are shown in Figure 8. Relatively low concentrations are
maintained for most of the year with far fewer occurrences of higher concentrations. For more
than 95% of the time hourly average SO2 concentrations of less than 200 μg/m3 prevail. Hourly
average concentrations in excess of the limit value are seen in the data record, but these occur
for far less than 1% of the time, indicating compliance with the NAAQS. Concentrations for the
99th percentile are shown for the three monitoring years in Table 16.
Table 16: Ambient hourly average concentrations of SO 2 for the 99th percentile (in μg/m3), together with the percentile at which the limit value was reached for the three monitoring years, at Kriel, Elandsfontein, and Komati monitoring stations.
Parameter 2010 2011 2012 NAAQS
limit value
Monitoring Station
Value of 99th percentile
266 μg/m3 219 μg/m3 263 μg/m3
350 μg/m3
Kriel Limit value reached at percentile
99.8% 99.6% 99.73%
Value of 99th percentile
184 μg/m3 217 μg/m3 197 μg/m3
Elandsfontein Limit value reached at percentile
99,9% 99,8% 99.97%
Value of 99th percentile
266 μg/m3 219 μg/m3 263 μg/m3
Komati Limit value reached at percentile
99.6% 99.7% 99.7%
25
(a.)
(b.)
(c.)
Figure 8: Frequency distribution of hourly average ambient SO 2 concentrations
measured at the Kriel Village (a.), Elandsfontein (b.), and Komati (c.) monitoring
stations from 2010 to 2012. The NAAQS limit value of 350 μg/m3 is shown by the
red horizontal line.
The daily (24-hour) average concentrations are shown in Figure 9. Here a similar pattern is
evident as with the hourly concentrations, with average concentrations for the bulk of the
monitoring period being seen to be relatively low. At Kriel Village monitoring station, the SO2
26
daily limit is exceeded in the monitoring record, but for less than 1% of the time and in fact not
at all during 2010. 99th percentile values were recorded of 82, 96 and 87 μg/m3 for each of the
years monitored (the limit value in the NAAQS is 125 µg/m3). At Elandsfontein, there is
compliance with the daily average SO2 NAAQS with 99th percentile values of 75, 84 and 80
μg/m3 for 2010, 2011 and 2012, respectively. At Komati, there is also compliance with the daily
average SO2 NAAQS with 99th percentile values of 97, 95 and 98 μg/m3 for 2010, 2011 and
2012 respectively.
Finally, but importantly, the annual averages for the three years of monitoring at Kriel are 23,
26 and 32 µg/m3 for 2010, 2011 and 2012, respectively against an annual limit of 50 μg/m3.
The annual averages for the 3 years of monitoring at Elandsfontein are 32, 38 and 34 µg/m3 for
2010, 2011 and 2012, respectively. The annual averages in each of the 3 years of monitoring
at Komati are 36, 33 and 37 µg/m3 for 2010, 2011 and 2012, respectively.
In summary ambient SO2 loading at the monitoring station is seen to follow a pattern of frequent
low concentrations and infrequent higher concentrations. No exceedances of the
1 hour, 24 hour or annual average NAAQS for SO2 are evident in the monitoring record
27
(a.)
(b.)
(c.)
Figure 9: Frequency distribution of daily (24-hour) average ambient SO2
concentrations measured at the Kriel Village (a.), Elandsfontein (b.), and Komati
(c.) monitoring stations from 2010 to 2012. The NAAQS limit value of 125 μg/m3
is shown by the red horizontal line.
28
Particulate Matter
Frequency distributions of measured ambient 24-hour PM10 concentrations are shown in Figure
10. It can be seen that the daily limit of 75 μg/m3 effective from 2015 was exceeded in all years
at Kriel Village. However, it should be noted that data recovery for PM10 was poor in 2010 and
2011. The 99th percentile values of 118, 118 and 121 μg/m3 for 2010, 2011 and 2012 were
measured, respectively. At Elandsfontein, the daily NAAQS for PM10 is not complied with in
2010 and 2011 with the limit value being exceeded for more than 5% of the time in 2011. There
is compliance with the NAAQS in 2012. At Komati, it can be seen that the daily limit of 75 μg/m3
effective from 2015 was seriously exceeded as evidenced by the 99th percentile values of 167,
153 and 142 μg/m3 for 2010, 2011 and 2012, respectively.
In addition the annual average concentrations at Kriel Village all exceed the annual average
NAAQS limit value of 40 μg/m3 namely annual averages of 59, 45 and 56 μg/m3, 2010, 2011
and 2012, respectively. PM10 loading is high and sustained throughout the entire year. At
Elandsfontein, the annual average concentration of 49 μg/m3 in 2010 is an exceedance of the
NAAQS limit value but the annual average values for 25 and 15 μg/m3 for 2011 and 2012 are
seen to comply with the annual average limit of 40 μg/m3 and thereby the NAAQS. PM10 loading
was generally lower at Elandsfontein than the other monitoring stations and this is likely as a
result of the lack of proximity of the station to residential areas. At Komati, the annual average
concentrations all exceed the annual average NAAQS limit value of 40 μg/m3 namely annual
averages of 83, 62 and 68 μg/m3, 2010, 2011 and 2012, respectively. PM10 loading is high and
sustained throughout the year.
29
(a.)
(b.)
(c.)
Figure 10: Frequency distribution of daily average ambient PM 10 concentrations
measured at the Kriel Village (a.), Elandsfontein (b.), and Komati (c.) monitoring
stations from 2010 to 2012. The 2015 NAAQS limit value of 75 μg/m3 is shown by
the red horizontal line.
30
Nitrogen oxides
A frequency distribution of ambient hourly average concentrations of NO2 is shown in
Figure 11. It can be seen from the graph that at Kriel Village, the one-hour NO2 limit value is
only exceeded during 2012 with maximum values of 102, 134 and 205 μg/m3 recorded. The
99th percentile values for hourly average NO2 at Kriel Village were recorded at 64, 71 and 167
μg/m3 which shows that there is no threat of the NAAQS being exceeded. At Elandsfontein,
the limit value is exceeded during all three monitoring years but for less than 1% of the time
(0,2, 0,01, and 0,03% of the time) indicating compliance with the hourly average NO2 NAAQS.
Annual average NO2 concentrations of 17, 17 and 14 μg/m3 are evident for 2010, 2011 and
2012 at Elandsfontein, which complies with the NAAQS. At Komati, the limit value is not
exceeded at all during the monitoring period and in fact maximum values of 127, 108 and 107
μg/m3 (just more than half of the limit value) were recorded. The 99th percentile values for hourly
average NO2 were recorded at 70, 56 and 67 μg/m3 which shows that there is no threat at all
of the NAAQS being exceeded.
31
(a.)
(b.)
(c.)
Figure 11: Frequency distribution of hourly average ambient NO2 concentrations
measured at the Kriel Village (a.), Elandsfontein (b.), and Komati (c.) monitoring
stations from 2010 to 2012. The NAAQS limit value of 200 μg/m3 is shown by the
red horizontal line.
32
5.2.2 Source apportionment
The question that then arises is the extent to which Eskom contributes to the measured ambient
PM10 concentrations. Apportioning the sources of measured ambient concentrations is not a
straightforward exercise and as such is presented qualitatively rather than quantitatively in the
section that follows. Reference is made to Figures 12 in which average hourly concentrations
are shown, to present the diurnal cycle typically experienced in terms of concentrations of SO2,
NO2 and PM10 at the Kriel Village monitoring station. The use of domestic fuels for cooking and
space heating is a well-known phenomenon in South Africa, most notable in typically lower
income settlements, even where electricity may be available.
The pattern is one where ambient concentrations of PM10 are seen to start increasing from
about 4:00 am in the morning. For the most part, concentrations of SO2, which are typically
relatively low, either stay constantly low or increase slightly during this time. The pattern of
increased concentrations of PM10 continues until about 08:00 where after there is a dramatic
decrease in the PM10 concentrations towards midday. In the mid-afternoon, when PM10
concentrations are at their lowest, there is a marked increase in the SO2 concentration. As the
afternoon progresses, the SO2 concentration then decreases again against a backdrop of
marked increases in the PM10 (and NO2) concentrations from about 17:00. NO2 concentrations
increase gradually through the day, more rapidly from 17:00 to 19:00, and then decrease
through the night.
Figure 12: Average hourly SO2, NO2 and PM10 concentrations for June at Kriel Village
calculated over the period 2010 to 2013
The diurnal patterns described above can be explained as follows. During the night the
atmosphere becomes stable with inversions often occurring. When the atmosphere is stable,
emissions from power station stacks do not come to ground-level as they are released above,
and simply cannot penetrate, the stable layer of the atmosphere. In the early hours of the
morning residents start to make fires and these fires result in the sharp increases in PM10
concentrations evident in the monitoring record. Also, there is an increase in traffic, as people
start commuting to work, causing NO2 levels to rise slightly. Because the fires and vehicle
33
emissions are at ground level, the emissions are trapped by the stable atmosphere, at ground
level.
When the sun rises the heating of the earth’s surface sees the break-up of the surface inversion
and the start of turbulence and mixing in the atmosphere. That mixing sees a reduction in
ground level concentrations of PM10. The mixing gets deeper and deeper as the day
progresses until at some point in the afternoon the power station plume is brought to ground-
level. As the power station plume comes to ground, there is a significant increase in the SO2
concentration.
As the afternoon wears on the earth’s surface cools and the atmosphere becomes more stable
with reduced atmospheric mixing. The stable atmosphere results in the SO2 concentration
falling significantly as once again the power station plume is prevented from reaching the
ground. At about the same time the PM10 and NO2 concentrations are seen to increase as
people return home after work and light fires for cooking and heating. In these terms it can be
argued that almost all measured ambient SO2 derives from the power station at the Kriel Village
monitoring station, whereas most measured PM10 and NOx derives from other sources
especially domestic fuel burning and vehicles. Secondary aerosol formation does not appear
to contribute significantly to episodes of high PM concentrations, given the strong association
between high PM10 concentrations and emissions from surface sources. Measured ambient
NO2 concentration sources appear to be a combination of power station, vehicles and domestic
fuel use but with the latter two sources being far more significant.
5.3 Dispersion modelling
The approach to the dispersion modelling in this assessment is based on the requirements of
the DEA guideline for dispersion modelling (DEA, 2012c) and is described in detail in the Plan
of Study report (uMoya-NILU, 2013), made available during the public consultation process. An
overview of the dispersion modelling approach for Kriel Power Station is provided here.
5.3.1 Models used
A number of models with different features are available for air dispersion studies. The
selection of the most appropriate model for an air quality assessment needs to consider the
complexity of the problem and factors such as the nature of the development and its sources,
the physical and chemical characteristics of the emitted pollutants and the location of the
sources. This assessment is considered a level 2 assessment, according to the definition on
the dispersion modelling guideline (DEA, 2012c). The CALPUFF suite of models
(http://www.src.com/calpuff/calpuff1.htm) was therefore used. The U.S. EPA Guideline of Air
Quality Models also provides for the use of CALPUFF on a case-by-case basis for air quality
estimates involving complex meteorological flow conditions, where steady-state straight-line
transport assumptions are inappropriate.
CALPUFF is a multi-layer, multi-species non-steady-state puff dispersion model that simulates
the effects of time- and space-varying meteorological conditions on pollution transport,
transformation and removal. CALPUFF can be applied on scales of tens to hundreds of
kilometres. It includes algorithms for sub-grid scale effects (such as terrain impingement), as
well as, longer-range effects (such as pollutant removal due to wet scavenging and dry
deposition, chemical transformation, and visibility effects of particulate matter concentrations).
The Air Pollution Model (TAPM) (Hurley, 2000; Hurley et al., 2001; Hurley et al., 2002) is used
to model surface and upper air meteorological data for the study domain. TAPM uses global
gridded synoptic-scale meteorological data with observed surface data to simulate surface and
34
upper air meteorology at given locations in the domain, taking the underlying topography and
land cover into account. The global gridded data sets that are used are developed from surface
and upper air data that are submitted routinely by all meteorological observing stations to the
Global Telecommunication System of the World Meteorological Organisation. TAPM has been
used successfully in Australia where it was developed (Hurley, 2000; Hurley et al., 2001; Hurley
et al., 2002), and in South Africa (Raghunandan et al., 2007). It is considered to be an ideal
tool for modelling applications where meteorological data does not adequately meet
requirements for dispersion modelling. TAPM modelled output data is therefore used to
augment the site-specific surface meteorological data for upper air data for input to CALPUFF.
5.3.2 Model parameterisation
TAPM
In the northern Mpumalanga Highveld TAPM is set-up in a nested configuration of two domains.
The outer domain is 576 km by 408 km with a 12 km grid resolution and the inner domain is
144 km by 102 km with a 3 km grid resolution (Figure 13). Three years (2010-2012) of hourly
observed meteorological data from the SAWS station at Witbank and Eskom’s stations at
Phola, Komati, Kendal and Kriel are input to TAPM to ‘nudge’ the modelled meteorology
towards the observations. The nesting configuration ensures that topographical effects on
meteorology are captured and that meteorology is well resolved and characterised across the
boundaries of the inner domain.
Twenty-seven vertical levels are modelled in each nest from 10 m to 5 000 m, with a finer
resolution in the lowest 1 000 m. The vertical levels are 10, 25, 50, 75, 100, 150, 200, 250, 300,
350, 400, 450, 500, 600, 750, 1000, 1250, 1500, 1750, 2000, 2250, 2500, 3000, 3500, 4000,
4500 and 5000 m.
The 3-dimensional TAPM meteorological output on the inner grid hourly includes wind speed
and direction, temperature, relative humidity, total solar radiation, net radiation, sensible heat
flux, evaporative heat flux, convective velocity scale, precipitation, mixing height, friction
velocity and Obukhov length. The spatially and temporally resolved TAPM surface and upper
air meteorological data is used as input to the CALPUFF meteorological pre-processor,
CALMET.
CALPUFF
The CALMET grid (light blue square in Figure 13), which is 10 000 km2 is 100 km (west-east)
by 100 km (north-south). It is a subdomain of the TAPM inner grid. It consists of a uniformly
spaced receptor grid with 500 m spacing, giving 40 000 grid cells (200 X 200 grid cells).
In turn, the CALPUFF modelling domain of 3 600 km2 is 60 km (west-east) by 60 km (north-
south) and is centred on Kriel Power Station (Figure 13). It consists of a uniformly spaced
receptor grid with 500 m spacing, giving 14 400 grid cells (120 X 120 grid cells).
The topographical and land use for the respective modelling domains is obtained from the
dataset accompanying the CSIRO’s The Air Pollution Model (TAPM) modelling package. This
dataset includes global terrain elevation and land use classification data on a longitude/latitude
grid at 30-second grid spacing from the US Geological Survey, Earth Resources Observation
Systems (EROS) Data Centre Distributed Active Archive Centre (EDC DAAC).
35
Figure 13: TAPM and CALPUFF modelling domains for Kriel, showing the relative
locations of the meteorological stations
The parameterisation of key variables that are applied in CALMET and CALPUFF are indicated
in Table 17 and Table 18.
Table 17: Parameterisation of key variables for CALMET
Parameter Model value
12 vertical cell face heights (m) 0, 20, 40, 80, 160, 320, 640, 1000, 1500, 2000, 2500, 3000,
4000
Coriolis parameter (per second) 0.0001
Empirical constants for mixing height equation Neutral, mechanical: 1.41
Convective: 0.15
Stable: 2400
Overwater, mechanical: 0.12
Minimum potential temperature lapse rate (K/m) 0.001
Depth of layer above convective mixing height
through which lapse rate is computed (m)
200
Wind field model Diagnostic wind module
Surface wind extrapolation Similarity theory
Restrictions on extrapolation of surface data No extrapolation as modelled upper air data field is applied
Radius of influence of terrain features (km) 5
Radius of influence of surface stations (km) Not used as continuous surface data field is applied
Conversion of NOx to NO2 75%
36
Table 18: Parameterisation of key variables for CALPUFF
Parameter Model value
Chemical transformation Default NO2 conversion factor of 0.75 is applied (DEA, 2012c).
Wind speed profile Rural
Calm conditions Wind speed < 0.5 m/s
Plume rise Transitional plume rise, stack tip downwash, and partial plume penetration
is modelled
Dispersion CALPUFF used in PUFF mode
Dispersion option Dispersion coefficients use turbulence computed from micrometeorology
Terrain adjustment method Partial plume path adjustment
5.3.3 Model accuracy
Air quality models attempt to predict ambient concentrations based on “known” or measured
parameters, such as wind speed, temperature profiles, solar radiation and emissions. There
are however, variations in the parameters that are not measured, the so-called “unknown”
parameters as well as unresolved details of atmospheric turbulent flow. Variations in these
“unknown” parameters can result in deviations of the predicted concentrations of the same
event, even though the “known” parameters are fixed.
There are also “reducible” uncertainties that result from inaccuracies in the model, errors in
input values and errors in the measured concentrations. These might include poor quality or
unrepresentative meteorological, geophysical and source emission data, errors in the
measured concentrations that are used to compare with model predictions and inadequate
model physics and formulation used to predict the concentrations. “Reducible” uncertainties
can be controlled or minimised. This is achieved by making use of the most appropriate input
data, preparing the input files correctly, checking and re-checking for errors, correcting for odd
model behaviour, ensuring that the errors in the measured data are minimised and applying
appropriate model physics.
Models recommended in the DEA dispersion modelling guideline (DEA, 2012b) have been
evaluated using a range of modelling test kits (http://www.epa.gov./scram001). It is therefore
not mandatory to perform any modelling evaluations. Rather the accuracy of the modelling in
this assessment is enhanced by every effort to minimise the “reducible” uncertainties in input
data and model parameterisation.
For Kriel Power Station the reducible uncertainty in CALMET and CALPUFF is minimised by:
Using representative quality controlled observed hourly meteorological data to nudge
the meteorological processor to the actual values;
Using 3-years of spatially and temporally continuous surface and upper air
meteorological data field for the modelling domain;
Appropriate parameterisation of both models (Tables 17 and 18);
Using representative emission data;
Applying representative background concentrations to include the contribution of other
sources;
Using a competent modelling team with considerable experience using CALPUFF; and,
For the most part NO2 concentrations were over predicted by the model (in some cases
the predictions were considerable higher than the measured values) which seems
attributable to the rate assumed for the modelling at which NOx would be converted to
NO2.
37
Earlier in this report mention was made of model accuracy and reducible error. That does not
change the fact that there remains an obvious question as to how well the model predicts the
concentrations that are measured at the various monitoring stations. A comparison between
the measured and modelled concentrations is not straight forward because the measured
concentrations reflect all sources of pollution whereas the model can obviously only predict the
ambient concentrations that occur as a function of the emissions included in the model. Past
experience (especially in modelling air quality on the Highveld) has shown that is well-nigh
impossible to account from all the emissions that may manifest as ambient air quality
concentrations.
For this reason only emissions from the power station have been modelled. Despite the
complexity of the sources there are three specific power stations where modelled (predicted)
concentrations can be expected to be reasonably well correlated with ambient measurements.
These are Matimba Power Station and the monitoring station at Marapong, 2 km north-east of
the power station (SO2); Camden Power Station and the Camden monitoring station 2 km east
of the power station (SO2 and NO2) and Majuba Power Station and the Majuba monitoring
station 3 km east-south-east of the power station (SO2 and NO2). A comparison of the measured
and modelled concentrations on the basis of 99th percentile comparisons is summarised below.
The short-term (hourly and daily) 99th percentile values are generally predicted to within a factor
of 2, which is considered to be an acceptable level of accuracy for a dispersion model. In most
cases, the model has under-predicted the measured concentrations, which is to be expected
since the model only considers emissions from the power station, while in reality many sources
contribute to ambient levels. The model under-predicts annual average concentrations, which
again is to be expected as background levels are more significant for annual average
concentrations than for the shorter averaging periods. The model does not predict the high
frequency of low concentrations that are evident in the monitoring record, which has the effect
of reducing the accuracy of the predicted annual average concentrations.
Table 19: Comparison between measured and modelled concentrations for those power
stations where a reasonable correlation between the two can be expected. The range
derives from the three-year monitoring period where the best and worst correlation of
the three years is presented.
Station Pollutant and averaging time
Ratio of modelled to measured
concentrations, expressed as a %
Best Worst
Matimba -
Marapong SO2
1 hr 91% 54%
Daily 93% 340%
Annual 40% 20%
Camden and
Camden
SO2
1 hr 76% 60%
Daily 95% 80%
Annual 41% 29%
NO2 1 hr 104% 83%
Annual 27% 25%
Majuba and Majuba
SO2
1 hr 59% 30%
Daily 104% 77%
Annual 29% 23%
NO2 1 hr 99% 43%
Annual 25% 12%
* Numbers less than 100% indicate an under-prediction, with numbers greater than 100% indicating an over-prediction.
38
5.4 Modelled ambient concentrations
Three operational scenarios are assessed for Kriel Power Station:
Scenario 1: Current average emissions to assess the relative contribution to ambient
concentrations near the Kriel Power Station.
Scenario 2: Requested emission limits that Eskom believes are achievable at Kriel Power
Station, in to assess the likely ambient concentrations near the Kriel Power
Station.
Table 20: Current average emissions (tons/annum) and Eskom requested
emission limits (mg/Nm3) for Kriel Power Station
Pollutant Code Scenario 1: Current Actual Emission Scenario 2a: Requested Emission Limits
Rate (tons/annum) Conc. (mg/Nm3)
NOX Stack 1 50,272 1,600
Stack 2 50,272 1,600
SO2 Stack 1 56,167 2,800
Stack 2 56,167 2,800
PM10 Stack 1 7,610 350
Stack 2 7,610 350
The current actual emission rates (tons/annum) have been calculated from a station-specific
emission factor for NOx, and from mass balance based on the sulphur content in the coal for
SO2. PM emissions are continually measured using continuous emission (opacity) monitors.
The requested emission limits are the upper limit of expected emissions. Actual average
emissions need to be 30-40% lower than the emission limit to ensure that the emission limit is
consistently achieved.
5.4.1 Modelled operational scenarios
The 99th percentile predicted ambient SO2, NO2 and PM10 concentrations from the dispersion
modelling for Kriel Power Station for emission Scenarios 1 and 2 are presented as isopleth
maps over the modelling domain. The DEA (2012c) recommend the 99th percentile
concentrations for short-term assessment with the NAAQS since the highest predicted ground-
level concentrations can be considered outliers due to complex variability of meteorological
processes. In addition, the limit value in the NAAQS is the 99th percentile.
The impact assessment therefore compares the predicted 99th percentile concentrations with
the respective NAAQS (limit values and the permitted frequency of exceedance) for Scenarios
1 and 2, with consideration of populated areas in the modelling domain.
The predicted annual average concentration and the 99th percentile concentration at the points
of maximum ground-level impact for Actual Emissions and Requested Limits Scenarios are
presented in Table 21.
39
Table 21: Predicted annual average concentration and the 99 th percentile
concentration at the points of maximum ground-level impact for the Actual
Current Emissions and Requested Emission Limits.
SO2 (µg/m3)
Scenario 1: Actual Emissions Scenario 2a: Requested Emission
Limits
NAAQS Limit
Values
1-hour 113.3 305.4 350
24-hour 42.2 113.8 125
Annual 4.7 12.6 50
NO2 (µg/m3)
Scenario 1: Actual Emissions Scenario 2a: Requested Emission
Limits
NAAQS Limit
Values
1-hour 76.1 130.9 200
Annual 3.1 5.4 40
PM10 (µg/m3)
Scenario 1: Actual Emissions Scenario 2a: Requested Emission
Limits
NAAQS Limit
Values
24-hour 5.7 14.2 75
Annual 0.63 1.57 40
5.4.2 Scenario 1: Current actual emissions
Sulphur dioxide
For current SO2 emissions from Kriel, the predicted annual average SO2 concentration does
not exceed the annual NAAQS of 50 µg/m3 under current average emission rates (Figure 14
and Table 21). The predicted annual concentration at the point of highest ground-level impact
is 4.7 µg/m3. Similarly the 99th percentile of the predicted 24-hour SO2 concentrations does not
exceed the NAAQS of 125 µg/m3 (Figure 15 and Table 21). The 99th percentile of the predicted
1-hour SO2 concentrations also complies with the NAAQS of 350 µg/m3 (Figure 16 and Table
21). The concentration at the point of maximum ground-level impact is 161 µg/m3.
40
Figure 14: Annual average SO2 concentrations (µg/m3) resulting from actual emissions
from Kriel Power Station emissions (Scenario 1)
Figure 15: Predicted 99th percentile 24-hour average SO2 concentrations (µg/m3)
resulting from actual emissions from Kriel Power Station (Scenario 1)
41
Figure 16: Predicted 99th percentile hourly SO2 concentrations (µg/m3) resulting from
actual emissions from Kriel Power Station (Scenario 1)
PM10
The predicted annual average PM10 concentrations are low and well below the current and
future NAAQS limit values of 50 µg/m3 and 40 µg/m3, respectively for current emission rates
(Figure 17 and Table 21). Similarly the 99th percentile of the predicted ambient 24-hour
concentrations are low compared to the current 24-hour NAAQS limit value of 120 µg/m3 and
the future limit value of 75 µg/m3. No exceedances of either limit value are predicted. The
predicted 99th percentile value at the point of maximum ground-level impact is
3 µg/m3.
42
Figure 17: Annual average PM10 concentrations (µg/m3) resulting from actual
emissions from Kriel Power Station (Scenario 1)
Figure 18: Predicted 99th percentile 24-hour PM10 concentrations (µg/m3) resulting
from actual emissions from Kriel Power Station (Scenario 1)
Nitrogen dioxide
The predicted annual average NO2 concentration does not exceed the NAAQS of 40 µg/m3 for
current emission rates (Figure 19 and Table 21). At the point where the highest concentration
43
occurs it is 3.1 µg/m3. The 99th percentile of the maximum predicted 1-hour NO2 concentrations
does not exceed the NO2 NAAQS limit value of 200 µg/m3 (Figure 20 and Table 21). It is 76.1
µg/m3 at the point of highest ground-level concentration.
Figure 19: Annual average NO2 concentrations (µg/m3) resulting from actual
emissions from Kriel Power Station (Scenario 1)
Figure 20: 99th percentile concentration of the predicted maximum hourly NO2
concentrations (µg/m3) resulting from actual emissions from Kriel Power Station
(Scenario 1)
44
5.4.3 Scenario 2: Requested emission limits
Before presenting the Scenario 2 results, the reader is reminded that in reality, Kriel will
continue to operate as it does currently, and in that sense the requested emissions limits
become simply an administrative change (viz. how the license conditions are presented), rather
than an actual change. The ambient measurements in Kriel village show the real impact of
Kriel’s emissions. That notwithstanding, it is necessary to present this worst case scenario so
that decision-makers are aware of the ambient concentrations that could manifest as a result
of Kriel operating under the requested emissions limits.
Sulphur dioxide
The predicted annual average SO2 concentration does not exceed the NAAQS of 50 µg/m3 for
Eskom’s predicted SO2 emission limit (Figure 21 and Table 21). The value of 12.6 µg/m3 at the
point of maximum ground-level impact is somewhat higher than for current emissions. Similarly
the 99th percentile of the predicted 24-hour SO2 concentrations does not exceed the NAAQS
limit value of 125 µg/m3 (Figure 22 and Table 21). The 99th percentile of the predicted 1-hour
SO2 concentrations is also lower than the NAAQS limit value of 350 µg/m3 (Figure 23 and Table
21).
Figure 21: Annual average SO2 concentrations (µg/m3) resulting from Eskom’s
requested emission limit for Kriel Power Station (Scenario 2)
45
Figure 22: Predicted 99th percentile 24-hour SO2 concentrations (µg/m3) resulting from
Eskom’s requested emission limit for Kriel Power Station (Scenario 2)
Figure 23: Predicted 99th percentile hourly SO2 concentrations (µg/m3) resulting from
the requested emission limit for Kriel Power Station (Scenario 2)
46
PM10
For Eskom’s requested emission limits, the predicted annual average PM10 concentrations are
low and well below the 2015 NAAQS limit value of 40 µg/m3 (Figure 24, Table 21). Similarly
the 99th percentile of the predicted 24-hour concentrations are low compared to the 2015 24-
hour NAAQS of 75 µg/m3 (Figure 24, Table 21). Kriel’s PM emissions are not predicted to result
in non-compliance with the PM NAAQS.
Figure 24: Annual average PM10 concentrations (µg/m3) resulting from Eskom’s
requested emission limits for Kriel Power Station (Scenario 2)
47
Figure 25: Predicted 99th percentile 24-hour PM10 concentrations (µg/m3) resulting
from Eskom’s requested emission limits for Kriel Power Station (Scenario 2)
Nitrogen dioxide
The predicted annual average NO2 concentration for Eskom’s requested emissions does not
exceed the NAAQS limit value of 40 µg/m3 for current emission rates (Figure 26, Table 21).
The highest predicted concentration is somewhat higher than for current emissions and is 5.4
µg/m3. The 99th percentile of the maximum predicted 1-hour NO2 concentrations do not exceed
the NO2 NAAQS limit value of 200 µg/m3 (Figure 27, Table 21). The predicted concentration at
the point of maximum ground-level impact is higher than for current emissions and is 130.9
µg/m3.
48
Figure 26: Annual average NO2 concentrations (µg/m3) resulting from Eskom’s
requested emission limits for Kriel Power Station (Scenario 2)
Figure 27: 99th percentile concentration of the predicted maximum hourly NO2
concentrations (µg/m3) resulting from Eskom’s requested emission limits for Kriel
Power Station (Scenario 2a)
49
5.5 Modelled cumulative ambient concentrations for the Northern
Highveld
5.5.1 Modelled operational scenarios
The cumulative effect of emissions from all power stations in the Northern Highveld has been
assessed by modelling the following power stations in one domain: Kendal, Kriel, Matla, Duvha,
Komati, Arnot and Hendrina. Two scenarios have been considered:
Scenario 1: Current average emissions
Scenario 2: Requested alternative emission limits
The 99th percentile predicted ambient SO2, NO2 and PM10 concentrations are presented as
isopleth maps over the modelling domain in Figures 28 to 44. The predicted annual average
concentration and the 99th percentile concentration at the points of maximum ground-level
impact for Actual Current Emissions (Scenario 1) and Requested Emission Limits
(Scenario 2) are presented in Table 22.
Table 22: Predicted annual average concentration and the 99 th percentile
concentration at the points of maximum ground-level impact for the Actual
Current Emissions and Requested Emission Limits
SO2 (µg/m3)
Scenario 1: Actual Current
Emissions
Scenario 2: Requested
Emission Limits
NAAQS Limit Value
(µg/m3)
1-hour 224 589a 350
24-hour 108 284b 125
Annual 18 45 50
NO2 (µg/m3)
Scenario 1: Actual Current
Emissions
Scenario 2: Requested
Emission Limits
NAAQS Limit Value
(µg/m3)
1-hour 119 201c 200
Annual 8 13 40
PM10 (µg/m3)
Scenario 1: Actual Current
Emissions
Scenario 2: Requested
Emission Limits
NAAQS Limit Value
(µg/m3)
24-hour 9 23 75
Annual 1.3 3.2 40
Maximum number of exceedances: a: 596, b: 95, c: 3
5.5.2 Scenario 1: Current actual emissions
Sulphur dioxide
According to the model predictions, SO2 emissions from current operations the Northern
Highveld power stations (combined) do not result in non-compliance with ambient SO2
standards. For current emissions the predicted annual average SO2 concentration (which is 18
µg/m3 at the point of highest impact in the domain) is significantly less than the SO2 NAAQS of
50 µg/m3 (Figure 28 and Table 22). Similarly the 99th percentile of the predicted 24-hour SO2
concentrations does not exceed the NAAQS limit value of 125 µg/m3 (Figure 29 and Table 22).
At the point of maximum ground-level impact, the 99th percentile 1-hour SO2 concentration is
224 µg/m3, which is below the limit value of 350 µg/m3 (Figure 30 and Table 22).
50
Figure 28: SO2 Scenario 1 – Predicted annual average SO2 concentrations
(µg/m3) resulting from current emissions from Northern Highveld power stations
(combined)
Figure 29: SO2 Scenario 1 – 99th percentile concentration of the predicted 24-
hour SO2 concentrations (µg/m3) for current emissions from Northern Highveld
power stations (combined)
51
Figure 30: SO2 Scenario 1 – 99th percentile of the predicted 1-hour SO2
concentrations (µg/m3) resulting from current actual emissions from Northern
Highveld power stations (combined)
Nitrogen dioxide
For current emissions from the Northern Highveld power stations (combined), the predicted
annual average NO2 concentration (which is 8 µg/m3 at the point of highest impact in the
domain) is significantly less than the NO2 NAAQS of 40 µg/m3 (Figure 31 and Table 22). At the
point of maximum ground-level impact, the predicted 99th percentile of the 1-hour NO2
concentration is 119 µg/m3, which is below the NAAQS limit value of 200 µg/m3 (Figure 32 and
Table 22). Note that a conservative NO2 oxidation ratio of 0.75 was assumed. The NO2
concentrations may be over predicted.
52
Figure 31: NO2 Scenario 1 – Predicted annual average NO2 concentrations
(µg/m3) resulting from current actual emissions from Northern Highveld power
stations (combined)
Figure 32: NO2 Scenario 1 – 99th percentile of the predicted 1-hour NO2
concentrations (µg/m3) resulting from current actual emissions from Northern
Highveld power stations (combined)
53
PM10
For current emissions from the Northern Highveld power stations (combined) the predicted
annual average PM10 concentration (which is 1.3 µg/m3 at the point of highest impact in the
domain) is significantly less than the PM10 NAAQS of 40 µg/m3 (Figure 33 and Table 22). At
the point of maximum ground-level impact, the predicted 99th percentile 24-hour concentration
for PM10 is 9µg/m3, which is well below the NAAQS limit value of 75 µg/m3 (Figure 34 and Table
22).
Figure 33: PM10 Scenario 1 – Predicted annual average PM10 concentrations
(µg/m3) resulting from actual emission limits from Northern Highveld power
stations (combined)
54
Figure 34: PM10 Scenario 1 – 99th percentile of the predicted 24-hour PM10
concentrations (µg/m3) resulting from actual emission limits from Northern
Highveld power stations (combined)
5.5.3 Scenario 2: Requested emission limits
Sulphur dioxide
If all the Northern Highveld power stations emit continuously at the requested emission levels
the predicted annual average SO2 concentration (which is 45 µg/m3 at the point of highest
impact in the domain) is higher than for actual current emissions, however remains below the
annual SO2 NAAQS of 50 µg/m3 (Figure 35 and Table 22).
The 99th percentile of the predicted 24-hour SO2 concentrations is predicted to be above the
NAAQS limit value of 125 µg/m3 in a large area over the Northern Highveld (Figure 36 and
Table 22), with 95 exceedances of the limit at the point of maximum impact in the vicinity of
Hendrina Power Station (Figure 37). There is predicted to be non-compliance with the 1-hour
SO2 NAAQS over a smaller area extending from Kriel and Matla to Arnot Power Station. At the
point of maximum ground-level impact, the 99th percentile 1-hour SO2 concentration is 589
µg/m3, which is above the limit value of 350 µg/m3 (Figure 38 and Table 22), with 596
exceedances of the limit value (Figure 39).
55
Figure 35: SO2 Scenario 2 – Predicted annual average SO2 concentrations
(µg/m3) resulting from requested emissions limits from Northern Highveld power
stations (combined)
Figure 36: SO2 Scenario 2 – 99th percentile concentration (µg/m3 ) of the
predicted 24-hour SO2 concentrations for requested emissions from Northern
Highveld power stations (combined) [red line = NAAQS limit value]
56
Figure 37: SO2 Scenario 2 – 99th percentile of the predicted 1-hour SO2
concentrations (µg/m3) resulting from requested emission from Northern
Highveld power stations (combined) [red line = NAAQS limit value]
Figure 38: SO2 Scenario 2 – 99th percentile of the predicted 24-hour SO2
concentrations (µg/m3) – Number of exceedances of the NAAQS limit value
[within the boundary of the red line]
57
Figure 39: SO2 Scenario 2 – 99th percentile of the predicted 1-hour SO2
concentrations (µg/m3) – Number of exceedances of the NAAQS limit value
[within the boundary of the red line]
Nitrogen dioxide
For requested emission limits from the Northern Highveld power stations (combined), the
predicted annual average NO2 concentration (which is 13 µg/m3 at the point of highest impact
in the domain) is higher than for actual current emissions and significantly less than the NO2
NAAQS of 40 µg/m3 (Figure 40 and Table 22). At the point of maximum ground-level impact,
the predicted 99th percentile 1-hour concentration for NO2 is 201 µg/m3, which is just above the
NAAQS of 200 µg/m3 (Figure 41 and Table 23) (Figure 32).
58
Figure 40: NO2 Scenario 2 – Predicted annual average NO2 concentrations
(µg/m3) resulting from requested emission limits from Northern Highveld power
stations (combined)
Figure 41: NO2 Scenario 2 – 99th percentile of the predicted 1-hour NO2
concentrations (µg/m3) resulting from requested emission limits from Northern
Highveld power stations (combined)
59
Figure 42: NO2 Scenario 2 – 99th percentile of the predicted 1-hour NO2
concentrations (µg/m3) [white squares represent areas of marginal non-
compliance with NAAQS)
PM10
If all the Northern Highveld power stations emit continuously at the requested PM emission
levels, the predicted annual average PM10 concentration (which is 3.2 µg/m3 at the point of
highest impact in the domain) is somewhat higher than for actual current emissions, however
significantly less than the PM10 NAAQS of 40 µg/m3 (Figure 43 and Table 22). At the point of
maximum ground-level impact in the vicinity of Kriel and Matla Power Stations, the predicted
99th percentile 24-hour concentration for NO2 is 23 µg/m3, which is well below the NAAQS limit
value of 75 µg/m3 (Figure 44 and Table 22).
60
Figure 43: PM10 Scenario 2 – Predicted annual average PM10 concentrations
(µg/m3) resulting from requested emission limits from Northern Highveld power
stations (combined)
Figure 44: PM10 Scenario 2 – 99th percentile of the predicted 24-hour PM10
concentrations (µg/m3) resulting from requested emission limits from Northern
Highveld power stations (combined)
61
5.6 Analysis of Emissions’ Impact on Human Health
5.6.1 Potential health effects
As previously described the key atmospheric emissions from coal combustion at Kriel Power
Station are SO2, NOX and particulates and the NAAQS for these pollutants have already been
presented (see Section 1.3.2). The potential effect of these pollutants is described in the section
that follows.
Sulphur dioxide (SO2)
On inhalation, most SO2 only penetrates as far as the nose and throat, with minimal amounts
reaching the lungs, unless the person is breathing heavily, breathing only through the mouth,
or if the concentration of SO2 is high (CCINFO, 1998). The acute response to SO2 is rapid,
within 10 minutes in people suffering from asthma (WHO, 2005). Effects such as a reduction
in lung function, an increase in airway resistance, wheezing and shortness of breath, are
enhanced by exercise that increases the volume of air inspired, as it allows SO2 to penetrate
further into the respiratory tract (WHO, 1999). SO2 reacts with cell moisture in the respiratory
system to form sulphuric acid. This can lead to impaired cell function and effects such as
coughing, broncho-constriction, exacerbation of asthma and reduced lung function.
Nitrogen dioxide (NO2)
Exposure to NO2 is typically inhalation and the seriousness of the effects depend more on the
concentration than on the length of exposure. The site of deposition for NO2 is the distal lung
where NO2 reacts with moisture in the fluids of the respiratory tract to form nitrous and nitric
acids. About 80 to 90% of inhaled nitrogen dioxide is absorbed through the lungs (CCINFO,
1998). Nitrogen dioxide (present in the blood as the nitrite ion) oxidises unsaturated membrane
lipids and proteins, which then results in the loss of control of cell permeability. Nitrogen dioxide
caused decrements in lung function, particularly increased airway resistance. People with
chronic respiratory problems and people who work or exercise outside will be more at risk to
NO2 exposure (EAE, 2006).
Particulate Matter
Particulate Matter (PM) is a broad term used to describe the fine particles found in the
atmosphere, including soil dust, dirt, soot, smoke, pollen, ash, aerosols and liquid droplets. With
PM, it is not just the chemical composition that is important but also the particle size. Particle
size has the greatest influence on the behaviour of PM in the atmosphere with smaller particles
tending to have longer residence times than larger ones. PM is categorised, according to
particle size, into TSP, PM10 and PM2.5.
Total suspended particulates (TSP) consist of all sizes of particles suspended within the air
smaller than 100 micrometres (µm). TSP is useful for understanding nuisance effects of PM,
e.g. settling on houses, deposition on and discolouration of buildings, and reduction in visibility.
PM10 describes all particulate matter in the atmosphere with a diameter equal to or less than
10 µm. Sometimes referred to simply as coarse particles, they are generally emitted from motor
vehicles (primarily those using diesel engines), factory and utility smokestacks, construction
sites, tilled fields, unpaved roads, stone crushing, and burning of wood. Natural sources include
sea spray, windblown dust and volcanoes. Coarse particles tend to have relatively short
residence times as they settle out rapidly and PM10 is generally found relatively close to the
source except in strong winds.
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PM2.5 describes all particulate matter in the atmosphere with a diameter equal to or less than
2.5 µm. They are often called fine particles, and are mostly related to combustion (motor
vehicles, smelting, incinerators), rather than mechanical processes as is the case with PM10.
PM2.5 may be suspended in the atmosphere for long periods and can be transported over large
distances. Fine particles can form in the atmosphere in three ways: when particles form from
the gas phase, when gas molecules aggregate or cluster together without the aid of an existing
surface to form a new particle, or from reactions of gases to form vapours that nucleate to form
particles.
Particulate matter may contain both organic and inorganic pollutants. The extent to which
particulates are considered harmful depends on their chemical composition and size, e.g.
particulates emitted from diesel vehicle exhausts mainly contain unburned fuel oil and
hydrocarbons that are known to be carcinogenic. Very fine particulates pose the greatest health
risk as they can penetrate deep into the lung, as opposed to larger particles that may be filtered
out through the airways’ natural mechanisms.
In normal nasal breathing, particles larger than 10 μm are typically removed from the air stream
as it passes through the nose and upper respiratory airways, and particles between 3 μm and
10 μm are deposited on the mucociliary escalator in the upper airways. Only particles in the
range of 1 μm to 2 μm penetrate deeper where deposition in the alveoli of the lung can occur
(WHO, 2003). Coarse particles (PM10 to PM2.5) can accumulate in the respiratory system and
aggravate health problems such as asthma. PM2.5, which can penetrate deeply into the lungs,
are more likely to contribute to the health effects (e.g. premature mortality and hospital
admissions) than coarse particles (WHO, 2003).
5.6.2 Analysis
The potential impacts on human health have been assessed in this report by comparing the
measured and predicted ambient air quality with the published NAAQS. It can be seen from the
measured ambient air quality measurements that SO2 and NO2 comply with the NAAQS for the
various averaging periods, but PM10 is seen not to comply. Ambient air quality concentrations
resulting from Kriel’s operations predicted using a dispersion model are seen to comply
completely with the NAAQS for SO2, NO2 and PM10 concentrations. Drawing conclusions about
the potential human health effects of these concentrations is not straight forward but the
following can be stated with a reasonable degree of confidence.
Particulate Matter (PM)
The prevailing ambient concentrations of PM10 present a significant risk to human health given
that there are sustained, elevated concentrations with continued non-compliance with both
shorter and longer term averaging periods. The contribution of the power station to that health
risk is, however, negligible at worst. NOx and SO2 emissions from the power station contribute
to the overall PM10 load as they are converted to particulate form in the atmosphere, but the
diurnal patterning of ambient PM10 concentrations indicates that by far the dominant
contribution to PM10 peak concentrations is low (ground) level sources such as domestic fuel
use, motor vehicle emissions, biomass burning and others. This finding is in line with the
FRIDGE study that was completed in 2004, which included estimates that the relative
percentage health impact was between 64 and 69% as a result of domestic fuel use, versus
some 4% from coal fired boilers. Thus it can be stated with confidence that the Eskom
requested PM emissions limits will not result in significant additional health risk in the areas
potentially impacted upon by the emissions, and neither will full compliance with the MES, result
in a material reduction in the prevailing health risk.
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Nitrogen oxides
Both measured and predicted ambient NO2 concentrations are seen to be fully compliant with
the NAAQS and so while it cannot be argued that there is no health risk, the health risk posed
by NOx emissions must be considered permissible. It can thus be stated that Eskom’s
requested NOx emission limits will not result in deterioration in the health risk that prevails
currently. Full compliance with the MES would see a reduction in health risk simply by virtue
of reducing the NOx load, but the actual ambient concentrations are so far below the limit value
of the standard that it seems unlikely that this reduction in health risk would be in any way
significant.
Sulphur dioxide
Measured ambient concentrations of SO2 are seen to be fully compliant with the NAAQS.
Again, this compliance cannot be argued to imply no health risk, but it has to be accepted as
being a permissible health risk. The predicted ambient concentrations of SO2 as a function of
current emissions and requested emissions from the power station indicate full compliance with
the NAAQS. Areas of full compliance with the SO2 NAAQS are again deemed not to be free of
health risks necessarily but the health risks are considered to be permissible.
Cumulative Emissions for the Northern Highveld
Modelling results confirm that Eskom’s requested PM emission limits cumulatively will not result
in additional health risk in the areas potentially impacted upon by the emissions, as both the
annual average and 99th percentile 24-hour concentrations fall well below the NAAQS limit
values. A similar picture is presented for the cumulative NO2 emissions which also comply with
the NAAQS limit values and maximum permissible exceedences per annum, thus augmenting
the statement that Eskom’s requested NOx emission limits will not result in deterioration in the
health risk that currently prevails.
While cumulatively the annual average SO2 concentration falls within the NAAQS limit value,
the 99th percentile 24-hour and 1-hour concentrations do not, and significantly exceed the
permissible number of exceedences per annum. Thus, the risk exists of unacceptable potential
health risk. This finding, however, must be seen in the light that the predicted concentrations
are probably an exaggeration of what actually happens in practice because when the SO2
emission sources are combined, the model error brought about by modelling the maximum
emissions rates at the power stations individually, is exaggerated further still because the
chances of all the sources operating at the requested emissions limits for an entire year is highly
improbable if not impossible.
5.7 Analysis of Emissions’ Impact on the Environment
In terms of impact on the environment, the pollutants in question pose the risk of a variety of
potential non-health impacts. Of these impacts dry and wet acid deposition is considered to be
the most significant but there are also concerns around potential impacts on vegetation and
fauna. The most challenging part of assessing such impacts is the absence of defined damage
thresholds (i.e. defined concentrations at which damage is known to occur) especially in a
regulatory sense. As a result the assumption that is made here is that if there is compliance
with the NAAQS that the damage risk will be considered permissible.
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Various investigations have been conducted on regional acidification in both the Mpumalanga
Highveld and escarpment areas, without any clear evidence emerging of significant negative
impacts. These various investigations are cited in Josipovic (2009) who proceeded to
investigate whether ‘the impacts of emitted pollutants and relationally accumulated deposition
of acidic air pollutants eventually exceed the carrying capacity of the natural environment’. He
further goes on to argue that: [bearing in mind the stated uncertainties]1 ‘acidic pollution
originating from the central industrial Highveld is not a current environmental threat to the
environment in remote areas of South Africa, specifically the Mpumalanga Escarpment and
forestry areas, and by implication neither is it a threat to adjacent countries. However, zones
within north-west Mpumulanga and south to south east of the Witbank industrial area have
indicated as areas exceeding critical loads of acidification, due also to local districts of sensitive
soils. Although not extensive in spatial distribution, with one area only showing the highest
exceedance level, these results indicate that areas in the vicinity of the central industrial zone
that have susceptible soils are at risk of exceeding critical loads.’
It is therefore clear that long-term emissions of acidic gases such as SO2 and NO2 pose a risk
of acidification, but principally in areas of sensitive soils. Given the long-term nature of the
effect it must be recognized that there will be an overall reduction in SO2 and NO2 emissions in
the longer term across the fleet, as the RTS and older power stations are progressively
decommissioned. In addition the significance of the acidification risk has not been presented
so it is not possible to assess the potential consequences (biodiversity loss, reductions in land
potential and so forth) in any meaningful way. More importantly perhaps it is simply not possible
to weigh up the benefits of reduced acid gas emissions (that would occur if there was full
compliance with the MES) against the financial and non-financial costs of full MES compliance.
Decision-makers should recognize the acidification risk that would be associated with
approving the applications for postponement, recognizing the longer-term reduction in acid load
as power stations are decommissioned across the fleet.
1 As described in the PhD Thesis.
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6. Complaints
Kriel Power Stations does maintain a Complaints register. Any complaints that are received by
the power station are recorded in this register. Complaints are presented in Table 23.
Table 23: Complaints register for Kriel Power Station
Date Nature of the
complaint
Source of the
complaint Response measures taken
29-09-2010 Dust from the
ash dam
Maphuti
Boloka
Continuous dust suppression system has been
implemented. Fugitive Emission Monitoring to be
implemented from 01 April 2012.
7. Current or planned air quality management interventions
Section 3.2 details the current air quality management interventions implemented at the Kriel
Power Station. Emission reduction interventions (fabric filter plant retrofits) to achieve
compliance with the ‘existing’ and ‘new’ plant emission limits for PM are planned for the Kriel.
Refer to the motivation contained within Kriel’s Postponement Application for further details.
8. Compliance and Enforcement History
No compliance and enforcement actions have been undertaken against Eskom’s Kriel Power
Station within the last five years.
9. Additional Information
No additional information is necessary.
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10. Summary and conclusion
Eskom’s coal-fired Kriel Power Station in Mpumalanga Province has a base generation capacity
of 3 000 MW. Power generation is a Listed Activity in terms of Section 21 of the NEMAQA and
Kriel should comply with the prescribed Minimum Emission Standards (MES) for existing plants
by 2015 and for new plants by 2020. Eskom contends that full compliance with the MES is not
in the national interest, given the unintended negative consequences of full compliance. Kriel
already achieves the Sulphur dioxide (SO2) limit (MES for ‘existing plant’). However, Kriel
Power Station will not be able to comply with the ‘new plant’ MES for SO2, or with the ‘existing
plant’ or ‘new plant’ NOx MES.. Plans are underway to reduce Particulate Matter (PM)
emissions from Kriel so that Kriel will comply with the existing and new plant limits. However,
the emission reductions will only be fully realised by April 2025. The purpose of this AIR is to
present an assessment of the ambient air quality implications of the postponement application
and the requested emissions limits for human health and the environment.
An analysis of ambient SO2 concentrations measured at the Kriel Village (situated 7km east of
Kriel Power Station), Elandsfontein, and Komati monitoring stations, indicates compliance with
the hourly, daily and annual average NAAQS for SO2. Full compliance with the 10-minute
NAAQS for SO2 was recorded at Kriel Village Monitoring Station (10-minute data is not recorded
yet at the other monitoring stations). Ambient PM measured at Kriel, Komati and Elandsfontein
monitoring stations indicates non-compliance with both the daily and annual NAAQS However,
modelling shows that Kriel Power Station is seen to contribute only marginally to the measured
concentrations at all three monitoring sites, bearing in mind that the bulk of the contribution to
PM10 concentrations arises from low level sources, especially domestic fuel use. Ambient NOx
measured at Kriel Village, Elandsfontein, and Komati monitoring stations indicates full
compliance with the hourly and annual NO2 NAAQS.
Dispersion modelling shows that current emissions from Kriel Power Station do not result in
non-compliance with SO2, NOx or PM ambient air quality standards. Similarly, the requested
emission limits for NOx, PM and SO2 will not result in non-compliance with ambient air quality
standards.
Cumulatively, the modelled actual current emissions for Eskom’s Power Stations on the
Northern Highveld combined comply with the NAAQS for SO2, NOx and PM10 and in all cases
ambient concentrations are significantly lower than the NAAQS. If all the power stations in the
Northern Highveld emit continuously at the requested emission limits (a theoretical scenario),
predictions show that there will still be compliance with the PM and NOx NAAQS, and with the
annual average SO2 NAAQS. However, if power stations continuously emit at the requested
SO2 emission limits, there will be non-compliance with the 24-hour and 1-hour SO2
concentrations over fairly large regions in the Northern Highveld. The number of exceedences
per annum is also significantly higher than that permissible in terms of the NAAQS.
Modelling results confirm that Eskom’s requested PM emission limits cumulatively will not result
in additional health risk in the areas potentially impacted upon by the emissions, as both the
annual average and 99th percentile 24-hour concentrations fall well below the NAAQS limit
values. A similar picture is presented for the cumulative NO2 emissions which also comply with
the NAAQS limit values and maximum permissible exceedences per annum, thus augmenting
the statement that Eskom’s requested NOx emission limits will not result in deterioration in the
health risk that currently prevails.
While cumulatively the annual average ambient SO2 concentration falls within the NAAQS limit
value considering Eskom’s requested SO2 emission limits, the 99th percentile 24-hour and 1-
hour concentrations do not, and significantly exceed the permissible number of exceedences
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per annum. Thus, the risk exists of unacceptable potential health risk. This finding, however,
must be seen in the light that the predicted concentrations are probably an exaggeration of
what actually happens in practice because when the SO2 emission sources are combined, the
model error brought about by modelling the maximum emissions rates at the power stations
individually, is exaggerated further still because the chances of all the sources operating at the
requested emissions limits for an entire year is highly improbable if not impossible.
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11. References
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12. Formal Declarations